In behavioral health (BH), considerable resources are allocated to the basic, standard processes of conducting initial evaluations. Patients present to BH clinics much like they do to an emergency room or sick call; problems range from minor to severe, urgent to routine, administrative to medical needs. Triaging patients is required to determine an appropriate immediate disposition. The critical yield of the evaluation is actuarial data used to predict risk. Historically, this has not been optimized for either resource allocation or quality of care, resulting in delays in service, additional cost to provide care, and inconsistent scientific application of BH. This project originally proposed to apply decision algorithms to an automated intake system to directly address quality, cost and access limitations. The key tasks were: 1. Defining an explicit knowledge base used to make triage and assessment decisions. 2. Providing a detailed analysis of current best practices and evidence-based decision- making criteria. 3. Creating symbolic logic using the identified criteria. 4. Designing output that is useful to providers. 5. Systematically evaluating the decisions and logic against clinician judgment. 6. Integrating the outcome of the project with larger initiatives (BHAVRS, DCSP, CHCSII).